考虑能耗的城市轨道交通列车停站方案研究

Train Stopping Scheme of Urban Rail Transit Considering Energy Consumption

为解决城市轨道交通系统乘客需求量上升和列车运行能耗增加的问题,本文基于能量转换原理,推导列车牵引能耗的计算方法,构建以乘客总旅行时间和列车总牵引能耗最少为目标的列车停站方案优化模型。结合多目标遗传算法(NSGA-Ⅱ算法),设计引入优势基因结构概念的微进化算法,并以某城市轨道交通1号线为算例,用两种算法进行优化。结果表明:用微进化算法优化的停站方案相比于站站停方案,减少乘客总旅行时间702568min,降低列车总牵引能耗1561kWh。此外,相比于NSGA-Ⅱ算法,微进化算法能有效提高解的质量。研究结果可为运营管理部门进一步优化可持续发展的城轨列车停站方案提供参考。

To solve the problem of rising passenger demand and increasing energy consumption of train operation in urban rail transit system,this paper bases on the principle of energy conversion,deduces the calculation method of train traction energy consumption.It constructs an optimization model for train station placement with the objectives of minimizing total passenger travel time and total train traction energy consumption.Combine the multi-objective genetic algorithm(NSGA-II algorithm),a micro-evolution algorithm incorporating the concept of dominant gene structures is designed.Use Line 1 of an urban rail transit as an example to optimize with the two algorithms.The results show that the stopping scheme optimized by the micro-evolutionary algorithm reduces the total passenger travel time by 702,568 min and the total traction energy consumption of the train by 1,561 kWh compared with the station stopping scheme,and the microevolutionary algorithm improves the quality of the solution compared with the NSGA-II algorithm.The results of the study can provide a reference for the operation management to further optimize the sustainable urban rail train stopping scheme.